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Fuzzy Logic - artificial intelligence:
In the above logic, we have been concerned with truth whether propositions and sentences are true. But, with some natural language statements, it is difficult to assign a "true" or "false" value. For instance, is the sentence: "Prince Charles is tall" true or false? Some people may say true, and others may say false, so there is an underlying probability that we might also want to represent. This can be attaining with so-called "fuzzy" logics. As such, the originator of fuzzy logics, Lotfi Zadeh, advocates not thinking about specific fuzzy logics but rather thinking about "fuzzification" of current theories, and this is starting to play a part in Artificial Intelligence. The arrangement of logics with programming agents and theories of probability to reason in the light of uncertain knowledge are important areas of Artificial Intelligence research. Various representation schemes such as Stochastic Logic Programs have an aspect of both logic and probability.
Interpolation Search The next task is to implement a variable size decrease-and-conquer solution to search. See Levitin [2007] pp 190 for a detailed description of the interpol
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write a program in assembly language using emu8086 so that the input string can contain both lower and upper case letters and any other character and the output will be the reverse
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